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The data analysis software in GeoMx DSP supports easy visualization and interpretation of data. High-resolution images can be displayed alongside quantitative profiling data, allowing interaction with either dataset in real time.

How does GeoMx DSP work?

The assay relies on RNA probes coupled with photocleavable oligonucleotide tags. After hybridization of probes to slide-mounted formalin-fixed paraffin-embedded (FFPE) tissue sections, the oligonucleotide tags are released from discrete, chosen regions of the tissue via UV exposure. Released tags are quantitated using RNAseq or a standard nCounter assay, and counts are mapped back to tissue location, yielding a spatially resolved digital profile of analyte abundance.1

Steps 1. Stain 2. Select ROI 3. UV-Cleave 4. Collect and Dispense 5. Count shown in a timeline manner. There are illustrations of the process


Applications of GeoMx DSP2

  • Discover biomarkers that predict therapeutic response
  • Profile distinct regions or cell types within the tumor microenvironment
  • Uncover the mechanism of action of a drug
  • Explore which genes are affected by a drug in specific components of a tissue
  • Reveal molecular subtypes for diseases
  • Understand disease mechanisms and progression
  • Study preclinical models

Technical spotlight

Explore tissue heterogeneity through spatial transcriptomic profiling

With the goal of understanding and improving anti-tumor immune response in the TME, we used the GeoMx® DSP platform to examine the effects of anti-mPD-1 therapy on CD45+ immune cells and PanCK+ tumor cells within the TME of the subcutaneous (SC) MC38-NCI.TD1 murine colon carcinoma model.

Explore tissue heterogeneity through spatial transcriptomic profiling

Morphology marker stained MC38 NCI.TD1 tumor section demonstrates the regions of interest segmented into areas of illumination (AOIs) containing CD45+ immune cells in proximity to high- versus low-PanCK expressing tumor cells. Volcano plots show the transcriptomic modulation of such AOIs in isotype control and anti-mPD-1 antibody treated MC38-NCI.TD1 tumors.

Advantages of GeoMx DSP

Spatial resolution

Provides high-resolution spatial information, allowing researchers to analyze gene expression patterns at the cellular and subcellular levels within complex tissues. This spatial context is critical in understanding the functional organization and interactions between different cell types.

Multiplexed analysis

Supports multiplexed analysis, allowing the simultaneous measurement of up to 21,000+ RNA targets. This efficiency not only saves time and resources but also provides a more comprehensive view of the molecular landscape, facilitating a holistic understanding of gene expression patterns.

Cellular heterogeneity

Unlike bulk RNA analysis, GeoMx DSP enables the identification and profiling of individual cell types within a tissue sample. This is particularly valuable in heterogeneous tissues like tumors, where understanding the specific expression patterns of different cell populations is essential for precision medicine and biomarker discovery.

Compatibility with existing technologies

Designed to be compatible with other molecular analysis techniques, including traditional RNA sequencing. The seamless integration allows researchers to combine spatial information with high-throughput genomic data, providing a more comprehensive and complementary analysis.

Tissue architecture insights

Offers a detailed map of gene expression within the tissue architecture, providing insights into the organization and structure of biological samples. This information is crucial for uncovering spatial relationships and understanding how gene expression varies across different regions of a tissue.

Customizable panels

Researchers can design custom panels to target specific genes or pathways of interest, tailoring GeoMx DSP experiments to meet the unique requirements of their studies. This flexibility enhances the versatility of the platform for a wide range of research applications.

Biomarker discovery

 The spatially resolved approach of GeoMx DSP enhances the discovery of spatially associated biomarkers, which may be overlooked in bulk RNA analysis. This capability is essential for identifying potential therapeutic targets and diagnostic markers for diseases.

Clinical relevance 

Ability to analyze clinical samples, including FFPE tissues, makes it highly relevant for translational research and clinical studies. This feature extends the potential impact of GeoMx DSP in the development of diagnostic tools and personalized medicine.

Single-cell analysis

Allows for single-cell resolution, enabling the study of individual cells' unique gene expression profiles. This level of granularity is particularly valuable in unraveling the complexity of biological systems and can lead to more precise and targeted therapeutic interventions.

Data visualization tools

The platform is equipped with advanced data visualization tools that facilitate the interpretation of spatial gene expression data. Researchers can create detailed maps and visual representations that aid the intuitive and comprehensive analysis of complex biological samples.

GeoMx DSP FAQs


References

  1. National Cancer Institute’s Center for Cancer Research. NanoString GeoMX Digital Spatial Profiler (DSP). https://genomics.ccr.cancer.gov/ncounter-geo-mx-digital-spatial-profiling/
  2.  GeoMx® Digital Spatial Profiler. NanoString. https://nanostring.com/products/geomx-digital-spatial-profiler/geomx-dsp-overview/

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